如何通过基于行值创建新变量来重塑数据框以进行分析

Question

有没有一种方法可以通过为列名创建一个新变量并为结果创建一个变量来从 olddf 获取 newdf？谢谢。

olddf <- data.frame('A' = c('Z1','Z2','Z3'), 
                    'B' = c(100, 200, 500),
                    'C' = c(90, 50, 60),
                    'D' = c(NA, 50, NA))

newdf <- data.frame('A' = c('Z1','Z2','Z3','Z1','Z2','Z3'), 
                    'B' = c(100, 200, 500, 100, 200, 500),
                    'var' = c('C', 'C', 'C', 'D', 'D', 'D'),
                    'res' = c(90, 50, 60, NA, 50, NA))

Answer 1

library(reshape2)
melt(olddf, id.vars = c('A','B'), value.name = 'res')

Answer 2

您也可以从 tidyr:

做 pivot_longer

library(tidyverse)
pivot_longer(olddf, cols = c(C,D), names_to = "var", values_to = "res") %>%
  arrange(var)

结果：

# A tibble: 6 x 4
  A         B var     res
  <chr> <dbl> <chr> <dbl>
1 Z1      100 C        90
2 Z2      200 C        50
3 Z3      500 C        60
4 Z1      100 D        NA
5 Z2      200 D        50
6 Z3      500 D        NA

如何通过基于行值创建新变量来重塑数据框以进行分析

How to reshape a dataframe for analysis by creating new variables based on row values

r

reshape

dataframe